{
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"
    }
   },
   "cell_type": "markdown",
   "id": "381358dc-f338-4d00-ac2e-de36db59ade7",
   "metadata": {},
   "source": [
    "# 赛事背景\n",
    "\n",
    "随着企业持续产生的商品销量，其数据对于自身营销规划、市场分析、物流规划都有重要意义。但是销量预测的影响因素繁多，传统的基于统计的计量模型，比如时间序列模型等由于对现实的假设情况过多，导致预测结果较差。因此需要更加优秀的智能AI算法，以提高预测的准确性，从而助力企业降低库存成本、缩短交货周期、提高企业抗风险能力。\n",
    "\n",
    "# 赛事任务\n",
    "\n",
    "本次大赛提供了商品销量历史数据作为训练样本，参赛选手需基于提供的样本构建模型，预测商品未来三个月的销售量。\n",
    "\n",
    "# 评审规则\n",
    "\n",
    "1.数据说明\n",
    "\n",
    "本次比赛为参赛选手提供了2类数据：商品历史销量数据和商品月订单数据。商品历史需求销量数据提供了商品编码、日期、是否促销、商品销售量。商品月订单数据提供了商品编码、商品类型、月份、订单数量、商品月初和月末库存量。（label空值的含义表示该商品当天无销量）\n",
    "\n",
    "- 初赛提供了2018年2月1日至2020年12月31日的若干商品历史销量数据和订单数据，预测其2021年1月至3月的销量数据。\n",
    "\n",
    "- 决赛提供了2018年2月1日至2021年3月31日的若干商品历史销量数据和订单数据，预测其2021年4月至6月的销量数据。\n",
    "\n",
    "![图片.png](attachment:572ae818-7e72-4741-9502-955d1b9659a3.png)\n",
    "\n",
    "2.评估指标\n",
    "\n",
    "本模型依据提交的结果文件，采用评价指标为准确率。\n",
    "\n",
    "（1）计算每个月商品预测准确率\n",
    "\n",
    "（2）计算累计所有预测月份的商品平均准确率\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5917068-e92a-4d60-9479-1706f4089346",
   "metadata": {},
   "source": [
    "# 读取数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "3ab212ff-43b2-4e73-a8f9-aeba89f256cc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-14T13:26:18.817852Z",
     "iopub.status.busy": "2022-06-14T13:26:18.817186Z",
     "iopub.status.idle": "2022-06-14T13:26:18.881070Z",
     "shell.execute_reply": "2022-06-14T13:26:18.880534Z",
     "shell.execute_reply.started": "2022-06-14T13:26:18.817801Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import lightgbm as lgb\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.model_selection import StratifiedKFold\n",
    "from matplotlib.pyplot import plot, show\n",
    "\n",
    "\n",
    "LABEL = 'label'\n",
    "\n",
    "df_train = pd.read_csv('data/商品需求训练集.csv')\n",
    "df_train_order = pd.read_csv('data/商品月订单训练集.csv')\n",
    "df_train['date'] = pd.to_datetime(df_train['date'])\n",
    "df_train['year'] = df_train['date'].dt.year\n",
    "df_train['month'] = df_train['date'].dt.month\n",
    "df_train = df_train.groupby(['product_id', 'year', 'month'])[['is_sale_day', 'label']].sum().reset_index()\n",
    "df_train = df_train.merge(df_train_order, on=['product_id', 'year', 'month'], how='left')\n",
    "\n",
    "df_test = pd.read_csv('data/商品需求测试集.csv')\n",
    "df_test_order = pd.read_csv('data/商品月订单测试集.csv')\n",
    "df_test['date'] = pd.to_datetime(df_test['date'])\n",
    "df_test['year'] = df_test['date'].dt.year\n",
    "df_test['month'] = df_test['date'].dt.month\n",
    "df_test = df_test.groupby(['product_id', 'year', 'month'])[['is_sale_day']].sum().reset_index()\n",
    "df_test = df_test.merge(df_test_order, on=['product_id', 'year', 'month'], how='left')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "699b14b4-7c92-4e8f-b3a3-84d5324db6df",
   "metadata": {},
   "source": [
    "# 特征工程"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "e696d5ef-5b91-4853-98a9-621e9229e91b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-14T13:26:19.853323Z",
     "iopub.status.busy": "2022-06-14T13:26:19.852673Z",
     "iopub.status.idle": "2022-06-14T13:26:19.952778Z",
     "shell.execute_reply": "2022-06-14T13:26:19.952274Z",
     "shell.execute_reply.started": "2022-06-14T13:26:19.853270Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# feats = ['month', 'order', 'start_stock', 'end_stock']\n",
    "\n",
    "df = pd.concat([df_train, df_test])\n",
    "\n",
    "for i in range(1, 8):\n",
    "    for f in [LABEL, 'order', 'start_stock', 'end_stock']:\n",
    "        df[f+'_shift_%d'%i] = df.groupby('product_id')[f].shift(i+3)\n",
    "\n",
    "for i in range(4):\n",
    "    for f in ['order', 'start_stock', 'end_stock']:\n",
    "        df[f+'_shift_-%d'%i] = df.groupby('product_id')[f].shift(-i)\n",
    "\n",
    "for i in [3, 6]:\n",
    "    for f in [LABEL, 'order', 'start_stock', 'end_stock']:\n",
    "        df[f+'_mean_%d'%i] = df[[f+'_shift_%d'%i for i in range(1, i+1)]].mean(axis=1)\n",
    "        df[f+'_std_%d'%i] = df[[f+'_shift_%d'%i for i in range(1, i+1)]].std(axis=1)\n",
    "        df[f+'_median_%d'%i] = df[[f+'_shift_%d'%i for i in range(1, i+1)]].median(axis=1)\n",
    "\n",
    "le = LabelEncoder()\n",
    "df['type'] = le.fit_transform(df['type'])\n",
    "df['type'] = df['type'].astype('category')\n",
    "\n",
    "df['product_id'] = df['product_id'].astype('category')\n",
    "\n",
    "df_train = df[df[LABEL].notna()].reset_index(drop=True)\n",
    "df_test = df[df[LABEL].isna()].reset_index(drop=True)\n",
    "\n",
    "feats = [f for f in df_test if f not in ['year', 'label']]\n",
    "\n",
    "df_train[LABEL+'_log1p'] = np.log1p(df_train[LABEL])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "228b8eb4-1efb-469a-90ef-79817b32f103",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-14T13:26:34.471044Z",
     "iopub.status.busy": "2022-06-14T13:26:34.470462Z",
     "iopub.status.idle": "2022-06-14T13:26:34.500876Z",
     "shell.execute_reply": "2022-06-14T13:26:34.500270Z",
     "shell.execute_reply.started": "2022-06-14T13:26:34.470994Z"
    },
    "tags": []
   },
   "source": [
    "# 模型训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "39f0e143-9f0f-474f-a348-ae1e18181d79",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-14T13:32:07.508066Z",
     "iopub.status.busy": "2022-06-14T13:32:07.507632Z",
     "iopub.status.idle": "2022-06-14T13:32:07.512109Z",
     "shell.execute_reply": "2022-06-14T13:32:07.511501Z",
     "shell.execute_reply.started": "2022-06-14T13:32:07.508031Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "params = {\n",
    "    'learning_rate': 0.05,\n",
    "    'boosting_type': 'gbdt',\n",
    "    'objective': 'regression',\n",
    "    'metric': 'mse',\n",
    "    'verbose': -1,\n",
    "    'seed': 2222,\n",
    "    'n_jobs': -1,\n",
    "}\n",
    "\n",
    "fold_num = 5\n",
    "seeds = [2222]\n",
    "oof = np.zeros(len(df_train))\n",
    "importance = 0\n",
    "pred_y = pd.DataFrame()\n",
    "for seed in seeds:\n",
    "    kf = StratifiedKFold(n_splits=fold_num, shuffle=True, random_state=seed)\n",
    "    for fold, (train_idx, val_idx) in enumerate(kf.split(df_train[feats], df_train['product_id'])):\n",
    "        print('-----------', fold)\n",
    "        train = lgb.Dataset(df_train.loc[train_idx, feats],\n",
    "                            df_train.loc[train_idx, LABEL+'_log1p'])\n",
    "        val = lgb.Dataset(df_train.loc[val_idx, feats],\n",
    "                          df_train.loc[val_idx, LABEL+'_log1p'])\n",
    "        model = lgb.train(params, train, valid_sets=[val], num_boost_round=10000,\n",
    "                          callbacks=[lgb.early_stopping(100), lgb.log_evaluation(1000)])\n",
    "\n",
    "        oof[val_idx] += model.predict(df_train.loc[val_idx, feats]) / len(seeds)\n",
    "        pred_y['fold_%d_seed_%d' % (fold, seed)] = model.predict(df_test[feats])\n",
    "        importance += model.feature_importance(importance_type='gain') / fold_num\n",
    "\n",
    "df_train['target_weight'] = df_train[LABEL] / df_train.groupby(['year', 'month'])[LABEL].transform('sum')\n",
    "df_train['oof'] = np.expm1(oof)\n",
    "score1 = np.sum((1 - np.abs(df_train[LABEL]-df_train['oof']) / (df_train[LABEL])\n",
    "                 ) *\n",
    "                df_train['target_weight']) / 35\n",
    "print(score1)\n",
    "print(np.mean(np.abs(df_train[LABEL]-np.expm1(oof))/(df_train[LABEL]+1)))\n",
    "plot(df_train[LABEL])\n",
    "plot(np.expm1(oof))\n",
    "show()\n",
    "\n",
    "\n",
    "feats_importance = pd.DataFrame()\n",
    "feats_importance['name'] = feats\n",
    "feats_importance['importance'] = importance\n",
    "print(feats_importance.sort_values('importance', ascending=False)[:30])\n",
    "df_test[LABEL] = np.expm1(pred_y.mean(axis=1).values)\n",
    "\n",
    "df_test = df_test.sort_values(by=['month', 'product_id'])\n",
    "sub = pd.read_csv('data/提交示例.csv')\n",
    "sub[LABEL] = df_test[LABEL].values\n",
    "sub[LABEL] = sub[LABEL].map(lambda x: x if x >= 0 else 0)\n",
    "\n",
    "sub.to_csv('ans/baseline0613.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8cf3b3b0-7386-4d2e-ae88-3a7d333d5916",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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